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The paper addresses the problem of complexity in managing Decision Support Systems, due to the immense quantity of information available. With the increase in complexity, manual low level tasks take most of the decision experts’ time, not allowing them to focus on higher level business objectives, leading to poor quality of service and customer dissatisfaction. We treat a common manual low level task, the allocation of shared resources between groups of data warehouses. We describe how this task is executed in present, and propose a solution for rendering it autonomic while focusing on the improvement of the service levels. We base our proposal on the notions of autonomic computing, integration of specific heuristics and on aspects of ontology engineering as information source for knowledge base representation. The paper is aimed at proposing autonomic data warehouse resource configuration, with the applicative area of decision support systems.